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April 24, 2025

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Task API for web research

The Parallel Task API enables state-of-the-art web research at scale, with the highest quality at every price point. State your research task in natural language and Parallel will do the rest of the heavy lifting - generating input/output schemas, finding relevant URLs, extracting data in a structured format.

from parallel import Parallel
from pydantic import BaseModel, Field

class ProductInfo(BaseModel):
    use_cases: str = Field(
        description="A few use cases for the product."
    )
    differentiators: str = Field(
        description="3 unique differentiators for the product as a bullet list."
    )
    benchmarks: str = Field(
        description="Detailed benchmarks of the product reported by the company."
    )

client = Parallel()
result = client.task_run.execute(
    input="Parallel Web Systems Task API",
    output=ProductInfo,
    processor="core"
)

print(f"Product info: {result.output.parsed.model_dump_json(indent=2)}\n")
print(f"Basis: {'\n'.join([b.model_dump_json(indent=2) for b in result.output.basis])}")

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Python SDK

Our SDK is now available for Python, making it easy to implement Parallel into your applications. The Python SDK is at parity with our Task API endpoints and simplifies request construction and response parsing.

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Flexible Processors

When running Tasks with Parallel, choose between 5 processors - Lite, Base, Core, Pro, and Ultra. We’ve built distinct processor options so that you can optimize price, latency, and quality per task.

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Self-Serve Developer Platform

Platform is the home for Playground, API Keys, Docs, Billing, Usage, and more.

  • Run a research task from scratch or using a template from Task Library
  • Generate and manage API keys for secure integration
  • Manage billing details, auto-reload settings, and usage analytics
  • Access comprehensive guides to learn how to use the API